Classification involves making decisions about the categorisation of data. 

Data is often sorted into categories by characteristic.

Variation describes the differences observed around us in every measurable aspect of life, such as age, height, eye colour and temperature. 

Variation is fundamental and directly connected to the other four key ideas.

Expectation is a prediction based on patterns and differences in data.

Distribution is a shape or relationship that represents a whole dataset. Common features of the shape of a distribution include centre, symmetry and non-symmetry (i.e. skewness), most frequent values or categories, and spread. 

Categorical data might be represented by a bar graph that shows how the data is distributed across the categories.

Numerical data might be displayed in a dot plot.

Randomness occurs when all possible outcomes of a situation have an equal chance of being selected.

An informal inference is a generalised claim that is formulated from the data collected (Watson n.d.).

Statistics is the process of answering questions using data. The data may need to be collected or may already exist. 

Five interconnected stages make up the statistical inquiry cycle:

• Problem

• Plan

• Data 

• Analysis

• Conclusion

Please refer to pages 50-55 for more information on each of the above stages as well as the different types of data, data tools, data displays and data measures.